Marco J. Van De Wiel

Numerical simulation of bank erosion and channel migration in meandering rivers

A numerical model of river morphology for meander bends with erodible cohesive banks is herein developed and tested. The new model has three key features. First, it couples a two-dimensional depth-averaged model of flow and bed topography with a mechanistic model of bank erosion. Second, it simulates the deposition of failed bank material debris at and its subsequent removal from the toe of the bank. Finally, the governing conservation equations are implemented in a moving boundary fitted coordinate system that can be both curvilinear and nonorthogonal. This simplifies grid generation in curved channels that experience bank deformation, allowing complex planform shapes associated with irregular natural channels to be simulated. Model performance is assessed using data from two flume experiments and a natural river channel. Results are encouraging, but the model underpredicts the scour depth in pools adjacent to the outer bank and, consequently, underpredicts bank migration rates.

Self-organized criticality in river basins: Challenging sedimentary records of environmental change

For many years researchers have linked increases in sediment and bedload from drainage basins to external factors such as increased rainfall. However, natural systems have always shown a high degree of scatter or nonlinearity in this response, which has made prediction of sediment yields difficult. We identify and describe a mechanism for self-organized criticality in the bedload sediment output from a simple drainage basin evolution model. This implies that identical floods will give considerably different sediment yields, which effectively renders the system unpredictable. Therefore, existing empirical methods for estimating sediment yields may need to be radically reevaluated. Furthermore, sedimentary records used to infer past climate or environmental conditions could simply reflect the internal system dynamics instead of external drivers.

Numerical Modeling of Bed Topography and Bank Erosion along Tree-lined Meandering Rivers

Numerical modeling of vegetation effects on open channel flow can follow one of three approaches. Each approach allows a specific range of flow features to be simulated. Computational hydraulics models can be constructed to solve one -dimensional (1D) averaged flow momentum and continuity equations. These models can simulate the effects of vegetative resistance on bulk flow velocity and depth (de Saint-Venant equations). Computational fluid dynamics (CFD) models can be constructed to solve the 1D to 3D steady Reynolds-averaged-Navier-Stokes (RANS) equations. These models can resolve local flow and turbulence features of the temporally averaged turbulent flow field. Finally, unsteady RANS (URANS) and Large eddy simulation CFD models can be constructed to solve the unsteady 3D Navier-Stokes equations. These models can provide a complete description of the instantaneous unsteady 3D turbulent flow field, capturing organized large-scale unsteadiness and asymmetries (coherent structures) resulting from flow instabilities. The characterization of vegetative flow resistance in these models has and will continue to command the attention of both researchers and practitioners alike. For flow through vegetation, where the ratio of plant height K to flow depth d is greater than 0.5, resistance is generally due more to form drag of the vegetation than from bed shear. Emergent vegetation can also induce wave resistance from free surface distortion. Plant properties that affect form drag include the ratio K/d, the relative submergence (K ? d), plant density, distribution, and flexibility. Further complicating matters, unsteady nonuniform flow conditions often prevail, wake interference effects can reduce drag, and a variety of different riparian plant species are typically found in combination, which causes the spatial distribution of plant properties to vary greatly. While it is important to consider the various complexities of flow resistance encountered in fluvial channels, most of our current knowledge on vegetative flow resistance is derived from laboratory flume experiments of steady fully developed flow through simulated vegetation of uniform density within rigid boundary rectangular flumes. These investigations have related vegetative resistance parameters, such as drag coefficients, Mannings n values, and friction factors f, to plant properties, including height, density, and flexibility [e.g. Kouwen and Unny, 1973; Kouwen and Fathi-Moghadam, 2000; Wu et al., 2000; Stone and Shen, 2002]. Presently, computational hydraulics and steady RANS models are the most practical approaches for high Reynolds number fluvial hydraulics applications despite the rapid advancements in computational power and numerical algorithm development. Computational hydraulics models, although limited to the computation of bulk flow properties, are usually sufficient for flood studies. For these models, the bulk flow resistance parameter (e.g., Mannings n or the Darcy-Weisbach friction factor, f) can be modified to account for the measurable physical properties of vegetation based on empirical formulas [Darby, 1999]. Although computationally more intensive, steady RANS models allow resolution of the time-averaged turbulent flow field by adding source terms to the RANS and turbulence transport equations to account for vegetative drag effects. Steady RANS models have simulated 1D laboratory flume flows through simulated rigid vegetation corresponding to the laboratory measurements reported by Shimizu and Tsujimoto [1994] and Lopez and Garcia [1997, 1998; see also Lopez and Garcia, 2001; Neary, 2000, 2003; Choi and Kang, 2001]. Tsujimoto and Kitamura [1998] have incorporated a stem deformation model to extend 1D RANS simulations to flexible vegetation. Naot et al. [1996] and Fischer-Antze et al. [2001] have developed 3D RANS models for vegetated flows in compound channels with vegetation zones in riparian areas and flood plains. These models have enabled prediction of the effects of vegetation on sediment transport in fluvial channels [e.g., Okabe et al., 1997; Lopez and Garcia, 1998]. Mean flow features resolved by the steady RANS models include: (1) the suppression of the streamwise velocity profile in the vegetated zone, (2) the inflection of the velocity profile at the top of the vegetation zone, and (3) the vertical distribution of the streamwise Reynolds stress (turbulent shear), with its maximum value at the top of the vegetation zone. However, for some of the experimental test cases, these models have been less successful at predicting the streamwise turbulence intensity. Also, the bulge in the velocity profile that is sometimes present near the bed cannot be resolved. This feature has been observed for some test cases reported by Shimizu and Tsujimoto [1994] and Fairbanks and Diplas [1998] despite a uniform vertical plant density distribution. The present limitations of the RANS models are due mainly to spatial and temporal averaging, and possibly failure to model the effects of turbulence anisotropy. Some of these deficiencies may be offset somewhat through the treatment of the drag and weighting coefficients in the governing equations that account for vegetative drag effects. However, adopting non-universal drag coefficients or non-theoretical based weighting coefficients to make up for model deficiencies is not particularly desirable [see Lopez and Garcia, 1997; Neary, 2003]. The 1D RANS models eliminate streamwise or spanwise gradients in the flow field and vegetation layer by spatial averaging. The 3D models, while not spatial averaging, distribute the drag uniformly throughout the vegetation layer by introducing body force terms in the RANS equations. To date, neither 1D nor 3D models have actually simulated flow around individual stems. Due to this simplification, streamwise vortices (secondary motion), a suspected mechanism for momentum transfer that produces the near bed velocity bulge [Neary, 2000, 2003], cannot be simulated with any of the present RANS models. As a result of time averaging, RANS models also cannot capture the organized large-scale unsteadiness and asymmetries (coherent structures) resulting from turbulent flow instabilities due to unsteady shear and pressure gradients induced by vegetation. These coherent structures include: (1) the transverse and other secondary vortices described by Finnegan [2000], which occur at the top of the vegetation layer as a result of a Kelvin-Helmholtz instability due to the inflection of the streamwise velocity profile, and (2) 3D vortices produced by the complex interaction of the approach flow with the stem (e.g., horseshoe and necklace vortices) and the oblique vortex shedding in the wake of the stem due to spanwise pressure gradients. These unsteady vortices would also contribute, or possibly play a dominant role, in redistributing momentum and producing the near bed velocity bulge. The use of Reynolds stress transport (RST) modeling to account for turbulence anisotropy and its effects has received only limited numerical investigation [Choi and Kang, 2001] and its benefits are not yet apparent. The laboratory experiments by Nezu and Onitzuka [2001] demonstrate that riparian vegetation has significant effects on secondary currents due to turbulence anisotropy, which increases with Froude number. However, coherent structures may account for a significantly larger percentage of the total Reynolds stresses and anisotropy [Ge et al., 2003]. Under such circumstances, RST modeling would only have limited value. Future numerical modeling efforts will focus on advanced CFD modeling techniques-namely statistical turbulence models that directly resolve large scale, organized, unsteady structures in the flow and advanced numerical techniques for simulating flows around multiple flexible bodies. These would include unsteady 3D Reynolds-averaged Navier-Stokes models [URANS; Paik et al., 2003; Ge et al., 2003] and large eddy simulation models [Cui and Neary, 2002]. Such techniques will elucidate the large-scale coherent structures described above, their important role in vegetative resistance, and their interaction and feedback with Reynolds stresses and lift forces that initiate sediment transport and bed form development

Calculating flux to predict future cave radon concentrations

Cave radon concentration measurements reflect the outcome of a perpetual competition which pitches flux against ventilation and radioactive decay. The mass balance equations used to model changes in radon concentration through time routinely treat flux as a constant. This mathematical simplification is acceptable as a first order approximation despite the fact that it sidesteps an intrinsic geological problem: the majority of radon entering a cavity is exhaled as a result of advection along crustal discontinuities whose motions are inhomogeneous in both time and space. In this paper the dynamic nature of flux is investigated and the results are used to predict cave radon concentration for successive iterations. The first part of our numerical modelling procedure focuses on calculating cave air flow velocity while the second part isolates flux in a mass balance equation to simulate real time dependence among the variables. It is then possible to use this information to deliver an expression for computing cave radon concentration for successive iterations. The dynamic variables in the numerical model are represented by the outer temperature, the inner temperature, and the radon concentration while the static variables are represented by the radioactive decay constant and a range of parameters related to geometry of the cavity. Input data were recorded at Driny Cave in the Little Carpathians Mountains of western Slovakia. Here the cave passages have developed along splays of the NE-SW striking Smolenice Fault and a series of transverse faults striking NW-SE. Independent experimental observations of fault slip are provided by three permanently installed mechanical extensometers. Our numerical modelling has revealed four important flux anomalies between January 2010 and August 2011. Each of these flux anomalies was preceded by conspicuous fault slip anomalies. The mathematical procedure outlined in this paper will help to improve our understanding of radon migration along crustal discontinuities and its subsequent exhalation into the atmosphere. Furthermore, as it is possible to supply the model with continuous data, future research will focus on establishing a series of underground monitoring sites with the aim of generating the first real time global radon flux maps.

Regional morphometric and geomorphologic mapping of Martian landforms

Initial mapping of the Martian surface, based on stratigraphic markers identified from Viking imagery, resulted in the demarcation of broad planetary scale geological zones. Recent advances in image resolution have established the presence of many smaller surface elements superposed on the older geological zones, thereby indicating younger surface morphologies that are in contradiction with the older mapping. Moreover, the stratigraphic mapping technique is subjective and relatively cumbersome because of its reliance on visual interpretation of images. In this paper a new analytical technique is developed which uses morphometric analysis of the Martian elevation map (MOLA data) to automate delineation and mapping of landforms at the regional scale. The analysis relies on altitude, local relief and local watershed clustering to delineate the landforms, and applies statistical clustering to identify structures with similar properties. As a case study, the technique is applied to Atlantis and Gorgonum basins. Comparison of the delineated features with landforms visible on high-resolution THEMIS images illustrates the accuracy of the morphometric technique in delineating and classifying surface structures, and also permits interpretation of the origin and evolution of the landforms. Our results also show that morphometric data and morphologic evaluation can be combined into a single interpretation of the distribution of surface patterns. A new geomorphological map of the study area is produced and contrasted with the existing stratigraphic map.